=========================================================
Tutorial of *PageWiseAggregation*
=========================================================

| *PageWiseAggregation* class has the aggregated log as the member variable and has the method functions to get the information.

.. image:: pagewise_aggregation.png
 :scale: 70%
 :align: center

.. code-block:: python

    import openLA as la

    course_info, event_stream = la.start_analysis(files_dir="dataset_sample", course_id="A")

    operation_count = la.convert_into_page_wise(event_stream,
                                                invalid_seconds=10,
                                                timeout_seconds=30*60,
                                                user_id=event_stream.user_id()[:10],
                                                contents_id=event_stream.contents_id()[0],
                                                operation_name=operations,
                                                count_operation=True
                                                )


| The method functions in below table are available now.
| You can get the information of the log like ``pagewise_aggregation.num_users()``.
| The documentation is in :doc:`../scripts/pagewise_aggregation`

+-----------------------------+--------------------------------------------------------------+
| function                    | description                                                  |
+=============================+==============================================================+
| num_users                   | Get the number of users in the log                           |
+-----------------------------+--------------------------------------------------------------+
| user_id                     | Get the unique user ids in the log                           |
+-----------------------------+--------------------------------------------------------------+
| contents_id                 | Get the unique contents ids in the log                       |
+-----------------------------+--------------------------------------------------------------+
| operation_name              | Get the unique operation name in the log                     |
+-----------------------------+--------------------------------------------------------------+
| operation_count             | Get the count of each (or specified) operation in the log    |
+-----------------------------+--------------------------------------------------------------+
| reading_seconds             | Get the reading seconds in the log                           |
+-----------------------------+--------------------------------------------------------------+
| reading_time                | Get the reading time (seconds, minutes, or hours) in the log |
+-----------------------------+--------------------------------------------------------------+
| num_unique_pages            | Get the number of unique pages in the log                    |
+-----------------------------+--------------------------------------------------------------+
| unique_pages                | Get the unique page numbers in the log                       |
+-----------------------------+--------------------------------------------------------------+

If you want to process other than the above functions, you can get DataFrame type event stream by ``pagewise_aggregation.df`` and process with Pandas library.

.. code-block:: python

    import OpenLA as la
    import pandas as pd

    operations = ["NEXT", "PREV", "ADD MARKER"]

    course_info, event_stream = la.start_analysis(files_dir="dataset_sample", course_id="A")

    pagewise_aggregation = la.convert_into_page_wise(event_stream,
                                                     invalid_seconds=10,
                                                     timeout_seconds=30*60,
                                                     user_id=event_stream.user_id()[:10],
                                                     contents_id=event_stream.contents_id()[0],
                                                     operation_name=operations,
                                                     count_operation=True
                                                     )

    pagewise_df = pagewise_aggregation.df
    print(pagewise_df)
    """
        userid contentsid  pageno  reading_seconds  NEXT  PREV  ADD MARKER
    0       U1         C1       1             1233     7     0          0
    1       U1         C1       2               80     2     0          2
    2       U1         C1       3              374     1     0          0
    3       U1         C1       4               46     1     0          0
    ...     ...       ...       ...            ...    ...   ...        ...
    """


Example
=============

.. toctree::
   :maxdepth: 1

   ../jupyter_examples/example_pagewise